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Regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating artificial intelligence (AI). It is part of the broader regulation of algorithms. [1][2] The regulatory and policy landscape for AI is an emerging issue in jurisdictions worldwide, including for international organizations ...
The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. [ 1 ] This includes algorithmic biases, fairness, automated decision-making, accountability, privacy, and regulation. It also covers various emerging or potential future challenges such as machine ethics (how to make machines that behave ethically ...
Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), either refers to an artificial intelligence (AI) system over which it is possible for humans to retain intellectual oversight, or refers to the methods to achieve this. [1][2] The main focus is usually on the reasoning behind the decisions or ...
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1] Quick progress in the field of deep learning, beginning in 2010s, allowed neural networks to surpass many previous approaches in performance. [2 ...
Regulation of algorithms, or algorithmic regulation, is the creation of laws, rules and public sector policies for promotion and regulation of algorithms, particularly in artificial intelligence and machine learning. [1][2][3] For the subset of AI algorithms, the term regulation of artificial intelligence is used.
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1] Such machines may ...
Knowledge representation and reasoning (KRR, KR&R, KR²) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates ...
Ethics for design (the codes of conduct, standards and certification processes that ensure the integrity of developers and users as they research, design, construct, employ and manage artificial intelligent systems—see Robot Ethics and Law below). [19]
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